Publication Date : 2016-05-15
Author : Zhu, Z.Chen, Z.Chen, X.He, P.
Disaster Management Theme :
Disaster Type : Flood
Document Type : Research Paper
Languange : en
Link : https://www.researchgate.net/profile/Zhihe_Chen/publication/295083158_Approach_for_evaluating_inundation_risks_in_urban_drainage_systems/links/56d144dd08ae4d8d64a39ec3.pdf
Urban inundation is a serious challenge that increasingly confronts the residents of many cities, as well as policymakers. Hence, inundation evaluation is becoming increasingly important around the world. This comprehensive assessment involves numerous indices in urban catchments, but the high-dimensional and non-linear relationship between the indices and the risk presents an enormous challenge for accurate evaluation. Therefore, an approach is hereby proposed to qualitatively and quantitatively evaluate inundation risks in urban drainage systems based on a storm water management model, the projection pursuit method, the ordinary kriging method and the K-means clustering method. This approach is tested using a residential district in Guangzhou, China. Seven evaluation indices were selected and twenty rainfall-runoff events were used to calibrate and validate the parameters of the rainfall-runoff model. The inundation risks in the study area drainage system were evaluated under different rainfall scenarios. The following conclusions are reached. (1) The proposed approach, without subjective factors, can identify the main driving factors, i.e., inundation duration, largest water flow and total flood amount in this study area. (2) The inundation risk of each manhole can be qualitatively analyzed and quantitatively calculated. There are 1, 8, 11, 14, 21, and 21 manholes at risk under the return periods of 1-year, 5-years, 10-years, 20-years, 50-years and 100-years, respectively. (3) The areas of levels III, IV and V increase with increasing rainfall return period based on analyzing the inundation risks for a variety of characteristics. (4) The relationships between rainfall intensity and inundation-affected areas are revealed by a logarithmic model. This study proposes a novel and successful approach to assessing risk in urban drainage systems and provides guidance for improving urban drainage systems and inundation preparedness.